Efficient Packet Pattern Matching for Gigabit Network Intrusion Detection Using GPUs
Che‐Lun Hung, Chun‐Yuan Lin, Hsiao-Hsi Wang, Chin-Yuan Chang · 2012
With the rapid development of network hardware technologies and network bandwidth, the high link speeds and huge amount of threats poses challenges to network intrusion detection systems, which must handle the higher network traffic and perform more complicated packet processing. In general, pattern matching is a highly computationally intensive process part of network intrusion detection systems. In this paper, we present an efficient GPU-based pattern matching algorithm by leveraging the computational power of GPUs to accelerate the pattern matching operations to increase the over-all processing throughput. From the experiment results, the proposed algorithm achieved a maximum traffic processing throughput of 2.4 Gbit/s. The results demonstrate that GPUs can be used effectively to speed up intrusion detection systems.